Based on technology that OpenText gained when it earlier this year acquired Actuate, a provider of business intelligence and analytics software, Allen Bonde, vice president of product marketing and innovation for OpenText, says the goal is to allow end users with advanced data analytics skills to invoke a cloud service without having to wait for an internal IT organization to roll out a Big Data analytics application.

Making use of a Big Data analytics application that Actuate launched two years ago, Bonde says that OpenText is now making that application available as a service. End users will then be able to expose the result of the analytics processed in OpenText Big Data Analytics via REST application programming interfaces in order to be able to embed that data within a larger business process, says Bonde.

One of the things that sets OpenText apart in the cloud is that it owns 31 data centers. Rather than relying on a public cloud service, Bonde says that OpenText has fired up 23 instances of its Big Data analytics service that are fully managed by OpenText. As such, it’s a lot easier for end users that need to contend with compliance requirements to take advantage of Big Data analytics using a private cloud service versus a public cloud.

In addition, Bonde notes that rather than being priced based on the number of users of the cloud application, the OpenText service is priced based on the amount of data and the type of service contract selected. Specifically, pricing ranges from $18,000 per year for 50 million rows of data to $300,000 a year for up to a billion rows of data. There are also unlimited usage pricing options involving beyond a billion rows of data.

The simple fact of the matter is that when it comes to standing up Big Data analytics applications, most internal IT organizations don’t have the skills needed to build, deploy or even manage them. And yet, line of business users are clearly demanding access to more advanced analytics applications. While the OpenText service isn’t necessarily designed to meet the needs of hard-core data scientists, Bonde says it more than meets the needs of the average line of business analyst.

Rather than simply letting end users decide what path to Big Data analytics to pursue on their own, it might be in the best interest of internal IT organizations that will be ultimately be held accountable for governing those applications to exercise some influence over a decision that, rightly or wrongly, most line of business executives are clearly getting more comfortable making on their own.